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  <div class="headertitle"><div class="title">Supervised Trainers</div></div>
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<a name="details" id="details"></a><h2 class="groupheader"> </h2>
<p>Optimized algorithms to solve specialized supervised optimization problems. </p>
<p>A supervised problem consists of data with inputs and labels. Typical tasks are regression, ranking, or classification. </p>
<table class="memberdecls">
<tr class="heading"><td colspan="2"><h2 class="groupheader"><a id="nested-classes" name="nested-classes"></a>
Classes</h2></td></tr>
<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classshark_1_1_abstract_svm_trainer.html">shark::AbstractSvmTrainer&lt; InputType, LabelType, Model, Trainer &gt;</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Super class of all kernelized (non-linear) SVM trainers.  <a href="classshark_1_1_abstract_svm_trainer.html#details">More...</a><br /></td></tr>
<tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classshark_1_1_abstract_linear_svm_trainer.html">shark::AbstractLinearSvmTrainer&lt; InputType &gt;</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Super class of all linear SVM trainers.  <a href="classshark_1_1_abstract_linear_svm_trainer.html#details">More...</a><br /></td></tr>
<tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classshark_1_1_abstract_trainer.html">shark::AbstractTrainer&lt; Model, LabelTypeT &gt;</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Superclass of supervised learning algorithms.  <a href="classshark_1_1_abstract_trainer.html#details">More...</a><br /></td></tr>
<tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classshark_1_1_abstract_weighted_trainer.html">shark::AbstractWeightedTrainer&lt; Model, LabelTypeT &gt;</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Superclass of weighted supervised learning algorithms.  <a href="classshark_1_1_abstract_weighted_trainer.html#details">More...</a><br /></td></tr>
<tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classshark_1_1_c_svm_trainer.html">shark::CSvmTrainer&lt; InputType, CacheType &gt;</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Training of C-SVMs for binary classification.  <a href="classshark_1_1_c_svm_trainer.html#details">More...</a><br /></td></tr>
<tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classshark_1_1_epsilon_svm_trainer.html">shark::EpsilonSvmTrainer&lt; InputType, CacheType &gt;</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Training of Epsilon-SVMs for regression.  <a href="classshark_1_1_epsilon_svm_trainer.html#details">More...</a><br /></td></tr>
<tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classshark_1_1_fisher_l_d_a.html">shark::FisherLDA</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Fisher's Linear Discriminant Analysis for data compression.  <a href="classshark_1_1_fisher_l_d_a.html#details">More...</a><br /></td></tr>
<tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classshark_1_1_kernel_mean_classifier.html">shark::KernelMeanClassifier&lt; InputType &gt;</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Kernelized mean-classifier.  <a href="classshark_1_1_kernel_mean_classifier.html#details">More...</a><br /></td></tr>
<tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classshark_1_1_kernel_s_g_d_trainer.html">shark::KernelSGDTrainer&lt; InputType, CacheType &gt;</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Generic stochastic gradient descent training for kernel-based models.  <a href="classshark_1_1_kernel_s_g_d_trainer.html#details">More...</a><br /></td></tr>
<tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classshark_1_1_lasso_regression.html">shark::LassoRegression&lt; InputVectorType &gt;</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">LASSO Regression.  <a href="classshark_1_1_lasso_regression.html#details">More...</a><br /></td></tr>
<tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classshark_1_1_l_d_a.html">shark::LDA</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Linear Discriminant Analysis (<a class="el" href="classshark_1_1_l_d_a.html" title="Linear Discriminant Analysis (LDA)">LDA</a>)  <a href="classshark_1_1_l_d_a.html#details">More...</a><br /></td></tr>
<tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classshark_1_1_linear_regression.html">shark::LinearRegression</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Linear Regression.  <a href="classshark_1_1_linear_regression.html#details">More...</a><br /></td></tr>
<tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classshark_1_1_linear_s_a_g_trainer.html">shark::LinearSAGTrainer&lt; InputType, LabelType &gt;</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Stochastic Average Gradient Method for training of linear models,.  <a href="classshark_1_1_linear_s_a_g_trainer.html#details">More...</a><br /></td></tr>
<tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classshark_1_1_logistic_regression.html">shark::LogisticRegression&lt; InputVectorType &gt;</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Trainer for Logistic regression.  <a href="classshark_1_1_logistic_regression.html#details">More...</a><br /></td></tr>
<tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classshark_1_1_missing_feature_svm_trainer.html">shark::MissingFeatureSvmTrainer&lt; InputType, CacheType &gt;</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Trainer for binary SVMs natively supporting missing features.  <a href="classshark_1_1_missing_feature_svm_trainer.html#details">More...</a><br /></td></tr>
<tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classshark_1_1_optimization_trainer.html">shark::OptimizationTrainer&lt; Model, LabelTypeT &gt;</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Wrapper for training schemes based on (iterative) optimization.  <a href="classshark_1_1_optimization_trainer.html#details">More...</a><br /></td></tr>
<tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classshark_1_1_perceptron.html">shark::Perceptron&lt; InputType &gt;</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight"><a class="el" href="classshark_1_1_perceptron.html" title="Perceptron online learning algorithm.">Perceptron</a> online learning algorithm.  <a href="classshark_1_1_perceptron.html#details">More...</a><br /></td></tr>
<tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classshark_1_1_ranking_svm_trainer.html">shark::RankingSvmTrainer&lt; InputType, CacheType &gt;</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Training of an SVM for ranking.  <a href="classshark_1_1_ranking_svm_trainer.html#details">More...</a><br /></td></tr>
<tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classshark_1_1_regularization_network_trainer.html">shark::RegularizationNetworkTrainer&lt; InputType &gt;</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Training of a regularization network.  <a href="classshark_1_1_regularization_network_trainer.html#details">More...</a><br /></td></tr>
<tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classshark_1_1_r_f_trainer.html">shark::RFTrainer&lt; LabelType &gt;</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Random Forest.  <a href="classshark_1_1_r_f_trainer.html#details">More...</a><br /></td></tr>
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